Quality Assurance Lead (Russian)

You will lead quality checks for Russian AI training projects. The work includes reviewing AI-generated content and trainer or QA submissions against project guidelines, rubrics, and expected standards.

You will also help keep remote quality work consistent by giving written feedback, maintaining project materials, supporting contributors, and identifying recurring problems.

• Review Russian AI-generated content and trainer or QA submissions.
• Check accuracy, fluency, grammar, spelling, tone, cultural fit, meaning, formatting, and instruction-following.
• Give clear written feedback and escalate recurring or serious issues.
• Maintain style guides, trackers, FAQs, examples, and onboarding materials in Russian.
• Support onboarding, training, and quality alignment for remote contributors.
• Explain updates and workflow changes to trainers and QAs.
• Help improve Russian-language QA processes as they grow.

What It Pays and Takes

This is an intermediate-level, part-time contract role for someone who can make careful language judgments and support other remote contributors.

• $30 per hour.
• 20+ hours per week.
• Open to candidates in Armenia, Estonia, Georgia, Israel, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Tajikistan, and Uzbekistan.
• Fluent Russian with strong reading and writing skills.
• Strong English for following guidelines and communicating feedback.
• Experience in Russian writing, editing, translation, localization, content QA, annotation, or AI training.
• Strong knowledge of Russian grammar, spelling, punctuation, tone, register, and cultural context.
• Ability to spot awkward or unnatural wording and preserve meaning accurately.
• Comfort using remote tools such as Discord, Google Docs, and Google Sheets.
• Experience leading or supporting remote trainers, annotators, reviewers, editors, or QAs is strongly preferred.

How It Works

Apply on OpenTrain with your resume and then complete the application on the hiring site.

About AI Training Work

AI training is the human work behind systems that generate and understand text. Contributors review examples, rate model responses, and improve language quality so AI systems follow instructions and communicate clearly; experienced reviewers are paid for the judgment and subject knowledge they bring.